Improved assessment of left ventricular ejection fraction using artificial intelligence in echocardiography: A comparative analysis with cardiac magnetic resonance imaging

Sveric, Krunoslav Michael; Ulbrich, Stefan; Dindane, Zouhir; Winkler, Anna; Botan, Roxana; Mierke, Johannes; Trausch, Anne; Heidrich, Felix; Linke, Axel

doi:10.1016/j.ijcard.2023.131383

Cited by 6 publications

(2 citation statements)

References 30 publications

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“…The AI demonstrated greater accuracy and reliability compared to the MBS method, reducing user-related variability and, therefore, the potential to improve the clinical utility of echocardiography. This algorithm has gained approval from the Food and Drug Administration (FDA) and Conformité Européenne (CE) [ 34 ]. Another study was published about a deep learning model that was developed to detect region wall motion abnormalities.…”

Section: Resultsmentioning

confidence: 99%

Future Horizons: The Potential Role of Artificial Intelligence in Cardiology

Patrascanu,

Tutunaru,

Musat

et al. 2024

JPM

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Cardiovascular diseases (CVDs) are the leading cause of premature death and disability globally, leading to significant increases in healthcare costs and economic strains. Artificial intelligence (AI) is emerging as a crucial technology in this context, promising to have a significant impact on the management of CVDs. A wide range of methods can be used to develop effective models for medical applications, encompassing everything from predicting and diagnosing diseases to determining the most suitable treatment for individual patients. This literature review synthesizes findings from multiple studies that apply AI technologies such as machine learning algorithms and neural networks to electrocardiograms, echocardiography, coronary angiography, computed tomography, and cardiac magnetic resonance imaging. A narrative review of 127 articles identified 31 papers that were directly relevant to the research, encompassing a broad spectrum of AI applications in cardiology. These applications included AI models for ECG, echocardiography, coronary angiography, computed tomography, and cardiac MRI aimed at diagnosing various cardiovascular diseases such as coronary artery disease, hypertrophic cardiomyopathy, arrhythmias, pulmonary embolism, and valvulopathies. The papers also explored new methods for cardiovascular risk assessment, automated measurements, and optimizing treatment strategies, demonstrating the benefits of AI technologies in cardiology. In conclusion, the integration of artificial intelligence (AI) in cardiology promises substantial advancements in diagnosing and treating cardiovascular diseases.

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Section: Resultsmentioning

confidence: 99%

Future Horizons: The Potential Role of Artificial Intelligence in Cardiology

Patrascanu,

Tutunaru,

Musat

et al. 2024

JPM

View full text Add to dashboard Cite

show abstract

“…This information is crucial in diagnosing and managing heart diseases. For example, a study evaluating a novel AI for automated left ventricular ejection time calculation in echocardiography showed high accuracy, closely correlating with cardiac MRI results [121]. The AI, which demonstrated lower bias and greater reliability especially in challenging cases, outperformed conventional methods.…”

mentioning

confidence: 76%

The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century

Maleki Varnosfaderani,

Forouzanfar

2024

Bioengineering

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As healthcare systems around the world face challenges such as escalating costs, limited access, and growing demand for personalized care, artificial intelligence (AI) is emerging as a key force for transformation. This review is motivated by the urgent need to harness AI’s potential to mitigate these issues and aims to critically assess AI’s integration in different healthcare domains. We explore how AI empowers clinical decision-making, optimizes hospital operation and management, refines medical image analysis, and revolutionizes patient care and monitoring through AI-powered wearables. Through several case studies, we review how AI has transformed specific healthcare domains and discuss the remaining challenges and possible solutions. Additionally, we will discuss methodologies for assessing AI healthcare solutions, ethical challenges of AI deployment, and the importance of data privacy and bias mitigation for responsible technology use. By presenting a critical assessment of AI’s transformative potential, this review equips researchers with a deeper understanding of AI’s current and future impact on healthcare. It encourages an interdisciplinary dialogue between researchers, clinicians, and technologists to navigate the complexities of AI implementation, fostering the development of AI-driven solutions that prioritize ethical standards, equity, and a patient-centered approach.

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Artificial intelligence and myocarditis—a systematic review of current applications

Łajczak,

Jóźwik

2024

Heart Fail Rev

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Myocarditis, marked by heart muscle inflammation, poses significant clinical challenges. This study, guided by PRISMA guidelines, explores the expanding role of artificial intelligence (AI) in myocarditis, aiming to consolidate current knowledge and guide future research. Following PRISMA guidelines, a systematic review was conducted across PubMed, Cochrane Reviews, Scopus, Embase, and Web of Science databases. MeSH terms including artificial intelligence, deep learning, machine learning, myocarditis, and inflammatory cardiomyopathy were used. Inclusion criteria involved original articles utilizing AI for myocarditis, while exclusion criteria eliminated reviews, editorials, and non-AI-focused studies. The search yielded 616 articles, with 42 meeting inclusion criteria after screening. The identified articles, spanning diagnostic, survival prediction, and molecular analysis aspects, were analyzed in each subsection. Diagnostic studies showcased the versatility of AI algorithms, achieving high accuracies in myocarditis detection. Survival prediction models exhibited robust discriminatory power, particularly in emergency settings and pediatric populations. Molecular analyses demonstrated AI’s potential in deciphering complex immune interactions. This systematic review provides a comprehensive overview of AI applications in myocarditis, highlighting transformative potential in diagnostics, survival prediction, and molecular understanding. Collaborative efforts are crucial for overcoming limitations and realizing AI’s full potential in improving myocarditis care.

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Improved assessment of left ventricular ejection fraction using artificial intelligence in echocardiography: A comparative analysis with cardiac magnetic resonance imaging

Cited by 6 publications

References 30 publications

Future Horizons: The Potential Role of Artificial Intelligence in Cardiology

Future Horizons: The Potential Role of Artificial Intelligence in Cardiology

The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century

Artificial intelligence and myocarditis—a systematic review of current applications

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